Andrew Nichols
Generally this is how we think about incentives…
Why is this a problem?
Imagine policing as an example.
It was originally thought that you could model somones desire to engage in crime as a utilitiy function, and that, if you simply levied up the costs associated with engaging in a crime, you could incentivze a selfish optimizer to not commit a crime.
And here’s how that worked out
Contrast this with commmunity policing models, which incorporates the community and assumes social incentives to not engage in crime (this guy is passing out food and water to neighborhood kids).
Me: “Can you help me complete this survey?”
stranger: “Yeah sure.”
Me: “I’ll give you a quarter to help me complete this survey”
…
Stranger: “No thank you”
I’ll be adminstering a fake survey, in which I offer no compensation, “categorical” compensation, or high compensation. The prediction is that there will be almost a stepwise dropoff at very low values of compensation as compare to offering no compensation, but gradually the perceived material incentives will increase the frequency as the amounts get larger.
The model is sepcified like this:
\(probability(help) = \beta_0 + \beta_1offer + \beta_2offer^2 + \epsilon\)
Which is to say that i’ll be looking for a quadratic shape where the frequencies for no compenstation and high compenstation are greater than the frequencies for categorical compensation.
I would broadly expect…
\(\beta_1 < 0\) (the general downward drop representing the categorical effect)
\(\beta_2 > 0\) (the bend up representing the gradual dominance of the material incentives)
frequency - a one if they offered to help
female - a one if they appeared to be female
age - how old they were
ethinicity - what race/ethincity were they